Provide helper functions for package developers to create active bindings that looks like data embedded in the package, but are downloaded from remote sources.

Residual balancing is a robust method of constructing weights for marginal structural models, which can be used to estimate (a) the average treatment effect in a cross-sectional observational study, (b) controlled direct/mediator effects in causal mediation analysis, and (c) the effects of time-varying treatments in panel data (Zhou and Wodtke 2020 <doi:10.1017/pan.2020.2>). This package provides three functions, rbwPoint(), rbwMed(), and rbwPanel(), that produce residual balancing weights for estimating (a), (b), (c), respectively.

This package provides functions in this package will import filtered variant call format (VCF) files of SNPs data and generate data sets to detect copy number variants, visualize them and do downstream analyses with copy number variants(e.g. Environmental association analyses).

Read and write las and laz binary file formats. The LAS file format is a public file format for the interchange of 3-dimensional point cloud data between data users. The LAS specifications are approved by the American Society for Photogrammetry and Remote Sensing <https://community.asprs.org/leadership-restricted/leadership-content/public-documents/standards>. The LAZ file format is an open and lossless compression scheme for binary LAS format versions 1.0 to 1.4 <https://laszip.org/>.

Data for the examples and exercises in the book "R by Example". Jim Albert and Maria Rizzo (2012, ISBN 978-1-4614-1365-3).

Allows caching of raw data directly in R code. This allows R scripts and R Notebooks to be shared and re-run on a machine without access to the original data. Cached data is encoded into an ASCII string that can be pasted into R code. When the code is run, the data is automatically loaded from the cached version if the original data file is unavailable. Works best for small datasets (a few hundred observations).

Obtain information about countries around the globe. Information for names, states, languages, time, capitals, currency and many more. Data source are Wikipedia <https://www.wikipedia.org>, TimeAndDate <https://www.timeanddate.com> and CountryCode <https://countrycode.org>.

This is a analysis toolkit to streamline the analyses of minicircle sequence diversity in population-scale genome projects. rKOMICS is a user-friendly R package that has simple installation requirements and that is applicable to all 27 trypanosomatid genera. Once minicircle sequence alignments are generated, rKOMICS allows to examine, summarize and visualize minicircle sequence diversity within and between samples through the analyses of minicircle sequence clusters. We showcase the functionalities of the (r)KOMICS tool suite using a whole-genome sequencing dataset from a recently published study on the history of diversification of the Leishmania braziliensis species complex in Peru. Analyses of population diversity and structure highlighted differences in minicircle sequence richness and composition between Leishmania subspecies, and between subpopulations within subspecies. The rKOMICS package establishes a critical framework to manipulate, explore and extract biologically relevant information from mitochondrial minicircle assemblies in tens to hundreds of samples simultaneously and efficiently. This should facilitate research that aims to develop new molecular markers for identifying species-specific minicircles, or to study the ancestry of parasites for complementary insights into their evolutionary history. ***** !! WARNING: this package relies on dependencies from Bioconductor. For Mac users, this can generate errors when installing rKOMICS. Install Bioconductor and ComplexHeatmap at advance: install.packages("BiocManager"); BiocManager::install("ComplexHeatmap") *****.

This package provides a novel sufficient-dimension reduction method is robust against outliers using alpha-distance covariance and manifold-learning in dimensionality reduction problems. Please refer Hsin-Hsiung Huang, Feng Yu & Teng Zhang (2024) <doi:10.1080/10485252.2024.2313137> for the details.

Extension to REddyProc that allows reading data from netCDF files.

It provides a function for random number generation from members of the truncated multivariate elliptical family of distributions, including truncated versions of the Normal, Student-t, Pearson type VII, Slash, Logistic, and related distributions. Additional distributions can be specified by supplying the density generating function. The package also computes first- and second-order moments, including the covariance matrix, for selected distributions. References used for this package: Galarza, C. E., Matos, L. A., Castro, L. M., & Lachos, V. H. (2022). Moments of the doubly truncated selection elliptical distributions with emphasis on the unified multivariate skew-t distribution. Journal of Multivariate Analysis, 189, 104944 <doi:10.1016/j.jmva.2021.104944>; Ho, H. J., Lin, T. I., Chen, H. Y., & Wang, W. L. (2012). Some results on the truncated multivariate t distribution. Journal of Statistical Planning and Inference, 142(1), 25-40 <doi:10.1016/j.jspi.2011.06.006>; Valeriano, K. A., Galarza, C. E., & Matos, L. A. (2023). Moments and random number generation for the truncated elliptical family of distributions. Statistics and Computing, 33(1), 32 <doi:10.1007/s11222-022-10200-4>.

Implementation of the methods described in the paper with the above title: Langsrud, Ã . (2019) <doi:10.1007/s11222-018-9848-9>. The package can be used to generate synthetic or hybrid continuous microdata, and the relationship to the original data can be controlled in several ways. A function for replacing suppressed tabular cell frequencies with decimal numbers is included.

Extracts machine-readable variables from natural language text using AI APIs. Optimized for speed and cost efficiency through parallel processing and direct CSV-formatted responses from language models. Supports multiple AI providers with robust error handling and automatic retry mechanisms for failed extractions.

This package provides an interface to the Facebook API.

Fast C++ agglomerative hierarchical clustering algorithm packaged into easily callable R functions, designed to help cluster biological terms based on how similar of genes are expressed in their activation.

This package provides a collection of tools for measuring the similarity of text messages and tracing the flow of messages over time and across media.

This package provides functions for cleaning and summarising water quality data for use in National Pollutant Discharge Elimination Service (NPDES) permit reasonable potential analyses and water quality-based effluent limitation calculations. Procedures are based on those contained in the "Technical Support Document for Water Quality-based Toxics Control", United States Environmental Protection Agency (1991).

Computes confidence intervals for nonlinear functions of model parameters (e.g., product of k coefficients) in single-level and multilevel structural equation models. Methods include the distribution of the product, Monte Carlo simulation, and bootstrap methods. It also performs the Model-Based Constrained Optimization (MBCO) procedure for hypothesis testing of indirect effects. References: Tofighi, D., and MacKinnon, D. P. (2011). RMediation: An R package for mediation analysis confidence intervals. Behavior Research Methods, 43, 692-700. <doi:10.3758/s13428-011-0076-x>; Tofighi, D., and Kelley, K. (2020). Improved inference in mediation analysis: Introducing the model-based constrained optimization procedure. Psychological Methods, 25(4), 496-515. <doi:10.1037/met0000259>; Tofighi, D. (2020). Bootstrap Model-Based Constrained Optimization Tests of Indirect Effects. Frontiers in Psychology, 10, 2989. <doi:10.3389/fpsyg.2019.02989>.

Lightweight helpers for checking whether empirical results remain substantively unchanged across code revisions, platform differences, and package updates. The package supports regression-style testing of derived datasets, statistical model outputs, tables, and plots, helping researchers detect unintended result drift early and distinguish material from non-material changes in empirical workflows.

This package provides R and JavaScript functions to allow WebGL'-based 3D plotting using the three.js JavaScript library. Interactivity through roll-over highlighting and toggle buttons is also supported.

Supports modelling real-time case data to facilitate the real-time surveillance of infectious diseases and other point phenomena. The package provides automated computational grid generation over an area of interest with methods to map covariates between geographies, model fitting including spatially aggregated case counts, and predictions and visualisation. Both Bayesian and maximum likelihood methods are provided. Log-Gaussian Cox Processes are described by Diggle et al. (2013) <doi:10.1214/13-STS441> and we provide both the low-rank approximation for Gaussian processes described by Solin and Särkkä (2020) <doi:10.1007/s11222-019-09886-w> and Riutort-Mayol et al (2023) <doi:10.1007/s11222-022-10167-2> and the nearest neighbour Gaussian process described by Datta et al (2016) <doi:10.1080/01621459.2015.1044091>.

Implementation of the race/ethnicity prediction method, described in "rethnicity: An R package for predicting ethnicity from names" by Fangzhou Xie (2022) <doi:10.1016/j.softx.2021.100965> and "Rethnicity: Predicting Ethnicity from Names" by Fangzhou Xie (2021) <doi:10.48550/arXiv.2109.09228>.

Response surface designs with neighbour effects are suitable for experimental situations where it is expected that the treatment combination administered to one experimental unit may affect the response on neighboring units as well as the response on the unit to which it is applied (Dalal et al.,2025 <doi: 10.57805/revstat.v23i2.513>). Integrating these effects in the response surface model improves the experiment's precision Verma A., Jaggi S., Varghese, E.,Varghese, C.,Bhowmik, A., Datta, A. and Hemavathi M. (2021)<doi: 10.1080/03610918.2021.1890123>). This package includes sym(), asym1(), asym2(), asym3() and asym4() functions that generates response surface designs which are rotatable under a polynomial model of a given order without interaction term incorporating neighbour effects.

Designed for the import, analysis, and visualization of dosimetric and volumetric data in Radiation Oncology, the tools herein enable import of dose-volume histogram information from multiple treatment planning system platforms and 3D structural representations and dosimetric information from DICOM-RT files. These tools also enable subsequent visualization and statistical analysis of these data.